RE/RS, Data Understanding (MM)

Highlights

• Build high-quality multimodal datasets powering large model training runs.
• Synthesize images, audio, and video and measure impact on models.
• Advance data filtering, dedup, and quality control at massive scale.

What they offer

• Equity

Ideal candidate

Research-driven ML builder who loves data-centric problems and owns agendas end-to-end. Collaborative, empirical, and thoughtful about data quality, provenance, and AI impact.

Requirements

• Strong track record of new or improved ML ideas, through publications, projects, or applied research.
• Own and drive a research agenda, from choosing the right multimodal data problems to carrying long-running work through to impact.
• Excited by OpenAI's empirical, collaborative approach to research.